Laser scanners are often used in geometric reverse engineering to generate a CAD drawing out of an existing physical part. This often requires careful path planning to ensure the correct stand-off distance of the sensor, to prevent any collisions of the sensor with the target object and to prevent any scan occlusions in the resulting data. A dedicated system was constructed to collect data using a 3-axis cylindrical/prismatic device. The benefit of this scanning system is the ability to scan completely around the target object, including the bottom of the object. A stripe-type laser diode is used along with a CCD camera. The target object sits on a transparent plexi-glass table, which can be rotated 360 degrees. Both the laser and the CCD are mounted on an arm, such that they can be traversed along a linear path, as well as being rotated 360° around the table. This permits the device to scan in either spherical or cylindrical paths with 360° rotation around the target object. This system allows for the quick scanning of any object while minimizing the number of occlusions in the resulting scan data.
Application of current 3-D laser scanning systems to reverse engineering is limited by two obstacles. The meticulous guidance of the laser scanner over the surface of the object being scanned and the segmentation of the cloud data which is collected by the laser scanner. Presently, both obstacles are being manually solved. The guidance of the laser scanning sensor at the correct surface to sensor distance is dependent on operator judgement and the segmentation of the collected data is reliant on the user to manually define surface boundaries on a computer screen. By applying a 2-D CCD camera, both of these problems can be resolved. Depth information on the location of the object surface can be derived from a pair of stereo images from the CCD camera. Using this depth information, the scanner path can be automatically calculated. Segmentation of the object surface can be accomplished by employing a Kohonen neural network into the CCD image. Successful segmentation of the image is conditional on the locations selected to start neural nodes as well as the prevention of the neuron connectors from bleeding onto neighboring patches. Thus the CCD camera allows for the automatic path planning of the laser scanner as well as the segmentation of the surface into patches defined along its natural boundaries.
One of the road blocks on the path of automated reverse engineering has been the extraction of useful data from the copious range data generated from 3-D laser scanning systems. A method to extract the relevant features of a scanned object is presented. A 3-D laser scanner is automatically directed to obtain discrete laser cloud data on each separate patch that constitutes the object's surface. With each set of cloud data treated as a separate entity, primitives are fitted to the data resulting in a geometric and topologic database. Using a feed-forewarn neural network, the data is analyzed for geometric combinations that make up machine features such as through holes and slots. These features are required for the reconstruction of the solid model by a machinist or feature based CAM algorithms, thus completing the reverse engineering cycle.
KEYWORDS: 3D modeling, 3D vision, Data modeling, Computing systems, Manufacturing, Visual process modeling, Software development, Computer simulations, Machine vision, Sensors
This paper presents the development of a hardware and software system suitable for the three-dimensional (3-D) digitization and computer modeling of objects intended for manufacture through mold making via CNC machining or rapid tooling systems. The hardware sub-system is comprised of a three- dimensional (3-D) machine vision sensor integrated with a computer numerically controlled (CNC) machine tool. The software sub-system consists of modeling very large 3-D data sets (termed cloud data) using a unified, non-redundant triangular mesh. This representation is accomplished from the 3-D data points by a novel triangulation process. A case study is presented that illustrates the efficacy of the technique for rapid manufacture from an initial designer's model.
Two main problems currently face the developers of reverse engineering systems. The first is the time consuming digitization of 3D data. The second is the conversion of copious amounts of 3D digitized data into a concise data format exportable to CAD/CAM packages. Reverse engineering can be described as the automatic resolution of these problems. By combining the use of both a CCD camera and a 3D laser scanner, these issues can be tackled. The CCD camera is used to locate the object in the scan space, so that the laser scanner path can be programmed. Also, preliminary segmentation of the 2D image can be sued to identify individual surface segments to which a 3D laser scanner can then be directed to digitize. This extracted information can then be exported to a CAD/CAM package for the manipulation by the end user.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.